The push for reduced cost, more compact circuit boards, and added customer features has provided incentives for the inclusion of analog functions on primarily digital MOS integrated circuits (ICs) forming mixed-signal ICs. Single-chip designs combining digital and analog blocks built over a common substrate feature reduced levels of power dissipation, smaller package counts, and smaller package interconnect parasitics. The global analog/mixed signal market has expanded rapidly, doubling the size in six years from $31.7 billion in 2005 to over $60 billion in 2011.
The design of analog/mixed-signal systems, however, is a complicated task. There are many challenges in realizing mixed-signal ICs. One of the challenges is to minimize noise coupling between various parts of the system to avoid any malfunctioning of the system. In particular, noise coupled through the substrate has been identified as a major concern. Fast-switching logic components inject current into the substrate, causing voltage fluctuation. Because substrate bias strongly affects the transistor threshold voltage, voltage fluctuations can affect the operation of sensitive analog circuitry through the body effect. FIG. 3A illustrates this coupling mechanism. In the figure, a switching digital node 310 serves as a noise source and injects currents J1 (320) and J2 (330) into the substrate 340 which is connected to ground. A sensitive analog node 350 picks up the noise due to the varying local substrate potential Vb (360) caused by J2 (320). FIG. 3B illustrates this interaction from the circuit viewpoint. There are other known mechanisms for current injection into the substrate such as hot-carrier injection and parasitic bipolar transistors.
As technology and circuit design advance, substrate noise is beginning to plague even fully digital circuits. In these circuits, the cumulative effect of thousands or millions of logic gates changing state across the chip causes current pulses that are injected and absorbed into the substrate. Those currents are then transmitted to power and ground buses through direct feed-through and load charge and discharge. Such couplings are highly destructive because pulsing currents, partially injected into the substrate through impact ionization and capacitive coupling, can be broadcast over great distances and picked up by sensitive circuits through capacitive coupling and the body effect. The resulting threshold voltage modulation dynamically changes gate delays locally, affecting performance unpredictably. Switching noise is especially detrimental to dynamic logic, memories, and embedded analog circuits such as phase-locked loops. It can impair the performance of the integrated circuit, and even totally corrupt the functionality of the system.
It is thus important to develop modeling techniques that can predict the noise coupling before fabrication. One category of the conventional modeling techniques are based on formulating and numerically analyzing the substrate's electromagnetic interactions. A device simulator called Pisces is an example. While accurate, Pisces is not designed for circuit simulation. Some other simulators are based on solving differential equations numerically such as finite-element and finite difference methods. These methods perform a full domain discretization on the large but bounded substrate volume and may be able to handle large and dense designs. The computation cost, however, is still too high.
Another category of the conventional modeling techniques are formula-based. In one such technique, a macromodel with four parameters is constructed based on a physical understanding of the current flow paths in heavily doped substrates. These parameters can be determined using simple curve fitting from actual device measurements or device simulations for different distances of separation between the injection and sensing ports (contacts) on the substrate. These formula-based techniques are orders of magnitude faster than the numerical-analysis-based techniques because they directly evaluate mathematical expressions and can help designers to gain insight into the placement of various components before the final layout is done. Challenges, however, remain in developing fast and accurate macromodeling techniques that can be applied to not just simple but more complex geometric arrangements between noise sources and noise receivers.